Abstract
The article deals with the problem of segmentation of digital images, which is one of the main tasks in the field of digital image processing (IP) and computer vision. To solve this problem, an algorithm was proposed based on the use of a concept based on the theory of fuzzy sets. The main idea of the proposed algorithm is the formation of subsets of interconnected pixels based on the fuzzy-to-mean method. A distinctive feature of the proposed algorithm is the definition of a set of features that define areas with similar characteristics in the space of the characteristic features of the analyzed image. The proposed segmentation algorithm (SA) consists of two stages: 1) the formation of characteristic features for all channels of the base color; 2) clustering of image elements. The practical significance of the obtained results lies in the fact that the developed models of algorithms can be used in various applied problems, where the classification of objects represented as images is provided. To test the efficiency of the developed algorithm, experimental studies were carried out in solving a number of applied problems related to color image segmentation, in particular, license plate recognition problems.
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